Machine-Learning-Based Prediction of Exercise Intolerance of Patients With Heart Failure Using Pragmatic Submaximal Exercise Parameters
Using readily available parameters, ML methods can enable accurate prediction of low peak V̇O<sub>2</sub> in patients with HF.
Authors
- Tomohito Ohtani (ORCID: https://orcid.org/0000-0002-2963-7895)
- Taishi Kato
- Yasushi Sakata (ORCID: https://orcid.org/0000-0002-5618-4721)
- Hidetsugu Asanoi
Institutions
- Chiba-Nishi General Hospital (JP)
- The University of Osaka (JP)
Publication Details
- Journal
- Circulation Reports
- Published
- 2025-02-26
- DOI
- https://doi.org/10.1253/circrep.cr-24-0135
- Citations
- 2
- Primary Topic
- Cardiovascular and exercise physiology
- Type
- article
- Field-Weighted Citation Impact
- 4.76